Sr. Full Stack Engineer

For Those Who Work At Home, Georgia

We are seeking a specialist with experience designing, training, and operationalizing intelligent document-processing solutions. The ideal candidate combines applied AI and machine learning expertise with cloud data engineering, secure information handling, and configurable business-rule automation. This role focuses on turning unstructured and semi-structured documents into accurate, auditable, and actionable data products.

• Intelligent Document Processing (IDP), optical character recognition (OCR), and document classification
• Training, evaluating, and tuning document extraction models for structured, semi-structured, and handwritten content
• Entity and field extraction, confidence scoring, quality metrics, and model accuracy assessment
• Document preprocessing, page-level validation, exception detection, and human-in-the-loop review patterns
• Python development for data processing, automation, model integration, and reusable components
• Cloud-native data pipelines using object storage, analytical databases, batch processing, and job orchestration
• Configuration-driven validation using YAML or similar formats to separate business rules from application code
• Data normalization, reconciliation, tolerance handling, and comparison against authoritative data sources
• Encryption, decryption, sensitive-data controls, auditability, and secure cloud processing
• API and system integration for ingesting documents, publishing results, and supporting downstream workflows

• Practical experience with document AI platforms or comparable machine learning services
• Understanding of supervised model training, labeling strategies, evaluation datasets, confidence thresholds, and error analysis
• Ability to identify when OCR, rules-based logic, machine learning, or generative AI is the appropriate solution
• Experience applying large language models to document understanding, unstructured content analysis, summarization, or reasoning use cases
• Knowledge of responsible AI practices, including explainability, traceability, quality controls, and review escalation

• Experience with cloud object storage, SQL-based analytical platforms, and production data pipelines
• Batch and event-driven processing patterns, workflow orchestration, retries, monitoring, and operational support
• Data modeling for extracted values, confidence scores, validation results, and processing history
• CI/CD, source control, automated testing, environment promotion, and infrastructure-as-code practices
• Observability and troubleshooting across model, application, data, and integration layers

• Ability to translate document-review procedures into clear technical requirements and configurable validation rules
• Collaboration with business subject-matter experts to define fields, thresholds, exceptions, and acceptance criteria
• Clear documentation of model behavior, processing logic, decision outcomes, and operational procedures
• Ability to communicate complex AI and data-processing concepts to technical and non-technical stakeholders
• Focus on scalable, reusable solutions rather than one-off document automations

• Bachelor's Degree in Information Systems, Computer Science, Data Analytics, or related technical field
• Hands‑on experience delivering document‑processing or information‑extraction solutions in a regulated industry
• Experience with sensitive or confidential information and enterprise security controls
• Familiarity with cloud‑based machine learning and data platforms
• Knowledge of financial‑services, legal, healthcare, insurance, or other document‑intensive workflows
• Experience designing…